Meet the digital me

This is likely the most self-centered blogpost you will read today, maybe even this year. Because this post is all about me, the digital me.

Just like all people these days, I leave a digital footprint. I use apps, digital services and websites to share my experiences with others, keep people posted of what I do and compare what I do with all the stuff other people do.

This type of digital behaviour leaves a pretty big digital footprint, with copious amounts of data. Data that I can analyse and visualise to get to know me a little better.

R progamming language as a tool to analyse me

I have decided to collect, analyse and visualise digital data to get to know myself a bit better and practise my analytics skills. For all of the analysis and visualisation I will be using R as a language. In case you don’t know what R is or what you can do with this, I recommend doing a little Google Search and join the thousands of R users already working with this language. For all analysts, I believe knowing at least a bit about R stats should be required.

How will I get my data?

I will be using some pretty cool API’s to pull in data and also do some webscraping to get publicly available data to analyse. Some API’s are already available through R packages for me to leverage. This will make it pretty easy to get a clean dataset to work with. For webscraping I will use another R package called Rvest.

How will I visualise my data?

To visualise the digital me, I will also use R packages. ggplot2 and Plotly to start with, but I may experiment with some additional packages while I’m progressing the journey of getting to know the digital me.

Which part of me will I explore?

I will analyse myself by looking at the following services I often use:

  • Strava (I’m a cycling fan and use this to monitor my progress)
  • IMDB (because I rate movies after watching them)
  • Goodreads (my virtual bookshelf)
  • Spotify (people’s favorite digital jukebox)
  • Twitter (my chatter and babbles with others)